, Volume 104, Issue 3, pp 197207
First online:
Block coherence: a method for measuring the interdependence between two blocks of neurobiological time series
 Aatira G. NedungadiAffiliated withDepartment of Mathematics, Indian Institute of ScienceComputational Biology and Mathematical Modelling Group, Centre for Cellular and Molecular Biology
 , Mingzhou DingAffiliated withJ. Crayton Pruitt Family Department of Biomedical Enginerring, University of Florida
 , Govindan RangarajanAffiliated withDepartment of Mathematics and Centre for Neuroscience, Indian Institute of Science Email author
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Multisensor recordings are becoming commonplace. When studying functional connectivity between different brain areas using such recordings, one defines regions of interest, and each region of interest is often characterized by a set (block) of time series. Presently, for two such regions, the interdependence is typically computed by estimating the ordinary coherence for each pair of individual time series and then summing or averaging the results over all such pairs of channels (one from block 1 and other from block 2). The aim of this paper is to generalize the concept of coherence so that it can be computed for two blocks of nonoverlapping time series. This quantity, called block coherence, is first shown mathematically to have properties similar to that of ordinary coherence, and then applied to analyze local field potential recordings from a monkey performing a visuomotor task. It is found that an increase in block coherence between the channels from V4 region and the channels from prefrontal region in beta band leads to a decrease in response time.
Keywords
Coherence Spectral density matrix Multivariate process Granger causality Title
 Block coherence: a method for measuring the interdependence between two blocks of neurobiological time series
 Journal

Biological Cybernetics
Volume 104, Issue 3 , pp 197207
 Cover Date
 201103
 DOI
 10.1007/s0042201104297
 Print ISSN
 03401200
 Online ISSN
 14320770
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Coherence
 Spectral density matrix
 Multivariate process
 Granger causality
 Industry Sectors
 Authors

 Aatira G. Nedungadi ^{(1)} ^{(2)}
 Mingzhou Ding ^{(3)}
 Govindan Rangarajan ^{(4)}
 Author Affiliations

 1. Department of Mathematics, Indian Institute of Science, Bangalore, 560012, India
 2. Computational Biology and Mathematical Modelling Group, Centre for Cellular and Molecular Biology, Hyderabad, 500007, India
 3. J. Crayton Pruitt Family Department of Biomedical Enginerring, University of Florida, Gainesville, FL, 32611, USA
 4. Department of Mathematics and Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India